code: def _fresh_model(nfeatures, nusers, nitems, init=0.1):
      umat = np.full([nusers, nfeatures], init, dtype=np.float_)
      imat = np.full([nitems, nfeatures], init, dtype=np.float_)
      model = Model(umat, imat)
      model.initial_value = init
      assert model.feature_count == nfeatures
      assert model.user_count == nusers
      assert model.item_count == nitems
      return model
  
imports: import logging
  import time
  import pandas
  import numpy
  import numba
  from seedbank import numpy_rng
  from .bias import Bias
  from .mf_common import MFPredictor
  from ..None import util
label_desc: Use image node_id 1 for calling a global function with example usage: _fresh_model(nfeatures, nusers, nitems, init) and returns: model